R/cbaf-xlsxOutput.R
In armanshahrisa/cBioAutomatedTools: Automated functions for comparing various omic data from cbioportal.org
Defines functions
xlsxOutput
Documented in
xlsxOutput
#' @title Generate excel output for various studies/subgroups of a study.
#'
#' @description This function generates excel files containing gene validation
#' and all selected statistical methods. It uses outputs of
#' obtainOneStudy()/obtainMultipleStudies() and automatedStatistics() functions.
#'
#' @details
#' \tabular{lllll}{
#' Package: \tab cbaf \cr
#' Type: \tab Package \cr
#' Version: \tab 1.20.0 \cr
#' Date: \tab 2022-10-24 \cr
#' License: \tab Artistic-2.0 \cr
#' }
#'
#'
#'
#' @importFrom openxlsx createWorkbook addWorksheet writeData saveWorkbook
#'
#' @importFrom BiocFileCache bfcnew bfcquery bfcpath
#'
#' @importFrom utils head setTxtProgressBar txtProgressBar
#'
#'
#'
#' @include cbaf-obtainOneStudy.R cbaf-obtainMultipleStudies.R
#' cbaf-automatedStatistics.R
#'
#'
#'
#' @usage xlsxOutput(submissionName, transposeResults = FALSE)
#'
#'
#'
#' @param submissionName a character string containing name of interest. It is
#' used for naming the process.
#'
#' @param transposeResults a logical value that enables the function to replace
#' the columns and rows of data.
#'
#'
#'
#' @return It generates one excel file for each gene group. This excel file
#' contains output of automatedStatistics() and validation result from output of
#' either obtainOneStudy() or obtainMultipleStudies().
#'
#'
#'
#' @examples
#' genes <- list(K.demethylases = c("KDM1A", "KDM1B", "KDM2A", "KDM2B", "KDM3A",
#' "KDM3B", "JMJD1C", "KDM4A"), K.methyltransferases = c("SUV39H1", "SUV39H2",
#' "EHMT1", "EHMT2", "SETDB1", "SETDB2", "KMT2A", "KMT2A"))
#'
#' obtainOneStudy(genes, "test", "Breast Invasive Carcinoma (TCGA, Cell 2015)",
#' "RNA-Seq", desiredCaseList = c(3,4))
#'
#' automatedStatistics("test", obtainedDataType = "single study", calculate =
#' c("frequencyPercentage", "frequencyRatio"))
#'
#' xlsxOutput("test")
#'
#'
#'
#' @author Arman Shahrisa, \email{shahrisa.arman@hotmail.com} [maintainer,
#' copyright holder]
#' @author Maryam Tahmasebi Birgani, \email{tahmasebi-ma@ajums.ac.ir}
#'
#' @export
################################################################################
################################################################################
########## Generating excel file for the processed and validation data #########
################################################################################
################################################################################
xlsxOutput <- function(submissionName, transposeResults = FALSE){
##############################################################################
########## Prerequisites
# Check submissionName
if(!missing(submissionName)){
if(!is.character(submissionName)){
stop("[xlsxOutput] 'submissionName' must be a character string!")
}
} else{
stop("[xlsxOutput] 'submissionName' must be a character string!")
}
# Check transposeResults
if(!is.logical(transposeResults)){
stop("[xlsxOutput] 'transposeResults' must be either TRUE or FALSE!")
}
##############################################################################
########## Decide whether functions should stop now!
# Check wheather the requested data exists
database <-
system.file("extdata", submissionName, package="cbaf")
if(!dir.exists(database)){
stop("[xlsxOutput] Please run one of the obtainSingleStudy() or obtainMultipleStudies() functions first, and then the automatedStatistics() function!")
} else if(dir.exists(database)){
bfc <- BiocFileCache(
file.path(system.file("extdata", package = "cbaf"), submissionName),
ask = FALSE
)
if(!nrow(bfcquery(bfc, c("Parameters for automatedStatistics()"))) == 1){
stop("[xlsxOutput] Please run the automatedStatistics() function first!")
}
}
# obtain parameters for prevous function
previousFunctionParam <-
readRDS(
bfcpath(bfc, bfcquery(bfc, c("Parameters for automatedStatistics()"))$rid)
)
# fetch an old parameter from the previous function
desiredTechnique <- previousFunctionParam$desiredTechnique
cutoff <- previousFunctionParam$cutoff
obtainedDataType <- previousFunctionParam$obtainedDataType
# setting the value for cutoff
if(desiredTechnique == "methylation"){
cutoff.phrase <- "Mean methylation cutoff"
} else{
cutoff.phrase <- "log z-score cutoff"
}
# Store the new parameteres
newParameters <-list()
newParameters$submissionName <- submissionName
newParameters$transposeResults <- transposeResults
# Check wheather the requested data exists
number.of.rows.parameters <-
nrow(bfcquery(bfc, "Parameters for xlsxOutput()"))
if(number.of.rows.parameters == 1){
oldParameters <-
readRDS(bfcpath(bfc, bfcquery(bfc, c("Parameters for xlsxOutput()"))$rid))
# Check whether the previous function is skipped
if(previousFunctionParam$lastRunStatus == "skipped"){
if(identical(oldParameters, newParameters)){
continue <- FALSE
} else{
continue <- TRUE
}
} else{
continue <- TRUE
}
} else{
continue <- TRUE
}
# Getting the source data
statisticsData <-
readRDS(bfcpath(bfc, bfcquery(bfc, c("Calculated statistics"))$rid))
if(!is.list(statisticsData)){
stop("[xlsxOutput] Input database must be a list!")
}
# Check gene validation dat
if(obtainedDataType == "multiple studies"){
validationName <- "Validation data for multiple studie"
} else if(obtainedDataType == "single study"){
validationName <- "Validation data for single study"
}
if(nrow(bfcquery(bfc, validationName)) == 1){
validation.data <- readRDS(bfcpath(bfc, bfcquery(bfc, validationName)$rid))
}
# get the working directory
parent.directory <- getwd()
##############################################################################
########## Set the function ready to work
# Report
message("[xlsxOutput] Preparing excel file(s).")
# Count number of skipped excel files
skipped <- 0
# Create progressbar
total.number <- length(statisticsData)
heatmapOutputProgressBar <-
txtProgressBar(min = 0, max = total.number, style = 3)
ExtH <- 0
##############################################################################
########## Core segment
# Save heatmaps in separate folder
for(gr in seq_along(statisticsData)){
# Subset data that can be presented as heatmap
subset.name <- names(statisticsData)[gr]
if(is.null(subset.name)){
subset.name <- " "
}
subset.data <- statisticsData[[gr]]
sheet.names <- names(subset.data)
# merge with validation data
if(exists("validation.data")){
v.subset.name <- names(validation.data)[gr]
v.subset.data <- validation.data[[gr]]
if(identical(subset.name, v.subset.name)){
subset.data$Validation.Result <- v.subset.data
reorder <-
match(c("Validation.Result", sheet.names), names(subset.data))
subset.data <- subset.data[reorder]
}
}
# Create a directory and set it as desired folder
child.directory <-
paste0(gr, ". ", sub(x = subset.name, pattern = "\\.", replacement = "-"))
dir.create(
paste(parent.directory, child.directory, sep = "/"),
showWarnings = FALSE
)
setwd(paste(parent.directory, child.directory, sep = "/"))
# Initiating excel file creation
xo <- createWorkbook()
# determine ourput file name
name.of.excel.file <-
paste0(
gsub(x = subset.name, pattern = "\\.", replacement = "-"),
" (",
cutoff.phrase,
"=",
cutoff,
")" ,
".xlsx"
)
# Check if excel file already exists
if(continue | !continue & !file.exists(name.of.excel.file)){
hault <- FALSE
}else{
skipped <- skipped + 1
hault <- TRUE
}
for(possible in seq_along(subset.data)){
if(!hault){
# subset statistics
statistics.data <- subset.data[[possible]]
name.statistics.data <- names(subset.data)[possible]
if(name.statistics.data %in% c("Frequency.Percentage",
"Mean.Value",
"Median.Value")){
# Replace 'NaN' values with character string
statistics.data[is.nan(statistics.data)] <- "NaN"
# Replace 'NA' values with character string
statistics.data[is.na(statistics.data)] <- "NA"
}
# Saving the expression profile
## Replacing dots with space in sheet name
currentSheetName = gsub(
x = name.statistics.data,
pattern = "\\.",
replacement = " "
)
## Fixing the Max length of 31 characters for openxlsx package
currentSheetName = gsub(
x = currentSheetName,
pattern = "Top Genes of Frequency Percentage",
replacement = "Top Genes of Frequency Percenta"
)
## Save xlsx file
if(!transposeResults){
addWorksheet(xo, sheetName = currentSheetName)
writeData(xo, sheet = currentSheetName, x = statistics.data,
rowNames = TRUE)
} else if(transposeResults){
addWorksheet(xo, sheetName = currentSheetName)
writeData(xo, sheet = currentSheetName, x = t(statistics.data),
rowNames = TRUE)
}
}
# Update progressbar
ExtH <- ExtH + 1
setTxtProgressBar(heatmapOutputProgressBar, ExtH)
}
# Avoid removing previos xlsx file
if(file.exists(name.of.excel.file) & length(names(xo)) != 0){
file.remove(name.of.excel.file)
}
# Avoid storing empty workbook
if(length(names(xo)) != 0){
saveWorkbook(xo, name.of.excel.file)
}
}
# Close progressbar
close(heatmapOutputProgressBar)
# report number of skipped heatmaps
if(skipped > 0 & skipped != 1){
message("[xlsxOutput] ", as.character(skipped), " out of ", as.character(total.number), " excel files were skipped, because they already exist!")
} else if(skipped > 0 & skipped == 1){
message("[xlsxOutput] ", as.character(skipped), " out of ", as.character(total.number), " excel file was skipped, because it already exists!")
}
# Store the last parameter
oldParamXlsxOutput <- newParameters
# Store the parameters for this run
if(number.of.rows.parameters == 0){
saveRDS(
oldParamXlsxOutput,
file=bfcnew(bfc, "Parameters for xlsxOutput()", ext="RDS")
)
} else if(number.of.rows.parameters == 1){
saveRDS(
oldParamXlsxOutput,
file=bfc[[bfcquery(bfc, "Parameters for xlsxOutput()")$rid]]
)
}
# change directory to parent directory
setwd(parent.directory)
# message("[xlsxOutput] Finished.")
}
armanshahrisa/cBioAutomatedTools documentation built on Oct. 29, 2022, 2:38 p.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Defines functions xlsxOutput
Documented in xlsxOutput
#' @title Generate excel output for various studies/subgroups of a study.
#'
#' @description This function generates excel files containing gene validation
#' and all selected statistical methods. It uses outputs of
#' obtainOneStudy()/obtainMultipleStudies() and automatedStatistics() functions.
#'
#' @details
#' \tabular{lllll}{
#' Package: \tab cbaf \cr
#' Type: \tab Package \cr
#' Version: \tab 1.20.0 \cr
#' Date: \tab 2022-10-24 \cr
#' License: \tab Artistic-2.0 \cr
#' }
#'
#'
#'
#' @importFrom openxlsx createWorkbook addWorksheet writeData saveWorkbook
#'
#' @importFrom BiocFileCache bfcnew bfcquery bfcpath
#'
#' @importFrom utils head setTxtProgressBar txtProgressBar
#'
#'
#'
#' @include cbaf-obtainOneStudy.R cbaf-obtainMultipleStudies.R
#' cbaf-automatedStatistics.R
#'
#'
#'
#' @usage xlsxOutput(submissionName, transposeResults = FALSE)
#'
#'
#'
#' @param submissionName a character string containing name of interest. It is
#' used for naming the process.
#'
#' @param transposeResults a logical value that enables the function to replace
#' the columns and rows of data.
#'
#'
#'
#' @return It generates one excel file for each gene group. This excel file
#' contains output of automatedStatistics() and validation result from output of
#' either obtainOneStudy() or obtainMultipleStudies().
#'
#'
#'
#' @examples
#' genes <- list(K.demethylases = c("KDM1A", "KDM1B", "KDM2A", "KDM2B", "KDM3A",
#' "KDM3B", "JMJD1C", "KDM4A"), K.methyltransferases = c("SUV39H1", "SUV39H2",
#' "EHMT1", "EHMT2", "SETDB1", "SETDB2", "KMT2A", "KMT2A"))
#'
#' obtainOneStudy(genes, "test", "Breast Invasive Carcinoma (TCGA, Cell 2015)",
#' "RNA-Seq", desiredCaseList = c(3,4))
#'
#' automatedStatistics("test", obtainedDataType = "single study", calculate =
#' c("frequencyPercentage", "frequencyRatio"))
#'
#' xlsxOutput("test")
#'
#'
#'
#' @author Arman Shahrisa, \email{shahrisa.arman@hotmail.com} [maintainer,
#' copyright holder]
#' @author Maryam Tahmasebi Birgani, \email{tahmasebi-ma@ajums.ac.ir}
#'
#' @export
################################################################################
################################################################################
########## Generating excel file for the processed and validation data #########
################################################################################
################################################################################
xlsxOutput <- function(submissionName, transposeResults = FALSE){
##############################################################################
########## Prerequisites
# Check submissionName
if(!missing(submissionName)){
if(!is.character(submissionName)){
stop("[xlsxOutput] 'submissionName' must be a character string!")
}
} else{
stop("[xlsxOutput] 'submissionName' must be a character string!")
}
# Check transposeResults
if(!is.logical(transposeResults)){
stop("[xlsxOutput] 'transposeResults' must be either TRUE or FALSE!")
}
##############################################################################
########## Decide whether functions should stop now!
# Check wheather the requested data exists
database <-
system.file("extdata", submissionName, package="cbaf")
if(!dir.exists(database)){
stop("[xlsxOutput] Please run one of the obtainSingleStudy() or obtainMultipleStudies() functions first, and then the automatedStatistics() function!")
} else if(dir.exists(database)){
bfc <- BiocFileCache(
file.path(system.file("extdata", package = "cbaf"), submissionName),
ask = FALSE
)
if(!nrow(bfcquery(bfc, c("Parameters for automatedStatistics()"))) == 1){
stop("[xlsxOutput] Please run the automatedStatistics() function first!")
}
}
# obtain parameters for prevous function
previousFunctionParam <-
readRDS(
bfcpath(bfc, bfcquery(bfc, c("Parameters for automatedStatistics()"))$rid)
)
# fetch an old parameter from the previous function
desiredTechnique <- previousFunctionParam$desiredTechnique
cutoff <- previousFunctionParam$cutoff
obtainedDataType <- previousFunctionParam$obtainedDataType
# setting the value for cutoff
if(desiredTechnique == "methylation"){
cutoff.phrase <- "Mean methylation cutoff"
} else{
cutoff.phrase <- "log z-score cutoff"
}
# Store the new parameteres
newParameters <-list()
newParameters$submissionName <- submissionName
newParameters$transposeResults <- transposeResults
# Check wheather the requested data exists
number.of.rows.parameters <-
nrow(bfcquery(bfc, "Parameters for xlsxOutput()"))
if(number.of.rows.parameters == 1){
oldParameters <-
readRDS(bfcpath(bfc, bfcquery(bfc, c("Parameters for xlsxOutput()"))$rid))
# Check whether the previous function is skipped
if(previousFunctionParam$lastRunStatus == "skipped"){
if(identical(oldParameters, newParameters)){
continue <- FALSE
} else{
continue <- TRUE
}
} else{
continue <- TRUE
}
} else{
continue <- TRUE
}
# Getting the source data
statisticsData <-
readRDS(bfcpath(bfc, bfcquery(bfc, c("Calculated statistics"))$rid))
if(!is.list(statisticsData)){
stop("[xlsxOutput] Input database must be a list!")
}
# Check gene validation dat
if(obtainedDataType == "multiple studies"){
validationName <- "Validation data for multiple studie"
} else if(obtainedDataType == "single study"){
validationName <- "Validation data for single study"
}
if(nrow(bfcquery(bfc, validationName)) == 1){
validation.data <- readRDS(bfcpath(bfc, bfcquery(bfc, validationName)$rid))
}
# get the working directory
parent.directory <- getwd()
##############################################################################
########## Set the function ready to work
# Report
message("[xlsxOutput] Preparing excel file(s).")
# Count number of skipped excel files
skipped <- 0
# Create progressbar
total.number <- length(statisticsData)
heatmapOutputProgressBar <-
txtProgressBar(min = 0, max = total.number, style = 3)
ExtH <- 0
##############################################################################
########## Core segment
# Save heatmaps in separate folder
for(gr in seq_along(statisticsData)){
# Subset data that can be presented as heatmap
subset.name <- names(statisticsData)[gr]
if(is.null(subset.name)){
subset.name <- " "
}
subset.data <- statisticsData[[gr]]
sheet.names <- names(subset.data)
# merge with validation data
if(exists("validation.data")){
v.subset.name <- names(validation.data)[gr]
v.subset.data <- validation.data[[gr]]
if(identical(subset.name, v.subset.name)){
subset.data$Validation.Result <- v.subset.data
reorder <-
match(c("Validation.Result", sheet.names), names(subset.data))
subset.data <- subset.data[reorder]
}
}
# Create a directory and set it as desired folder
child.directory <-
paste0(gr, ". ", sub(x = subset.name, pattern = "\\.", replacement = "-"))
dir.create(
paste(parent.directory, child.directory, sep = "/"),
showWarnings = FALSE
)
setwd(paste(parent.directory, child.directory, sep = "/"))
# Initiating excel file creation
xo <- createWorkbook()
# determine ourput file name
name.of.excel.file <-
paste0(
gsub(x = subset.name, pattern = "\\.", replacement = "-"),
" (",
cutoff.phrase,
"=",
cutoff,
")" ,
".xlsx"
)
# Check if excel file already exists
if(continue | !continue & !file.exists(name.of.excel.file)){
hault <- FALSE
}else{
skipped <- skipped + 1
hault <- TRUE
}
for(possible in seq_along(subset.data)){
if(!hault){
# subset statistics
statistics.data <- subset.data[[possible]]
name.statistics.data <- names(subset.data)[possible]
if(name.statistics.data %in% c("Frequency.Percentage",
"Mean.Value",
"Median.Value")){
# Replace 'NaN' values with character string
statistics.data[is.nan(statistics.data)] <- "NaN"
# Replace 'NA' values with character string
statistics.data[is.na(statistics.data)] <- "NA"
}
# Saving the expression profile
## Replacing dots with space in sheet name
currentSheetName = gsub(
x = name.statistics.data,
pattern = "\\.",
replacement = " "
)
## Fixing the Max length of 31 characters for openxlsx package
currentSheetName = gsub(
x = currentSheetName,
pattern = "Top Genes of Frequency Percentage",
replacement = "Top Genes of Frequency Percenta"
)
## Save xlsx file
if(!transposeResults){
addWorksheet(xo, sheetName = currentSheetName)
writeData(xo, sheet = currentSheetName, x = statistics.data,
rowNames = TRUE)
} else if(transposeResults){
addWorksheet(xo, sheetName = currentSheetName)
writeData(xo, sheet = currentSheetName, x = t(statistics.data),
rowNames = TRUE)
}
}
# Update progressbar
ExtH <- ExtH + 1
setTxtProgressBar(heatmapOutputProgressBar, ExtH)
}
# Avoid removing previos xlsx file
if(file.exists(name.of.excel.file) & length(names(xo)) != 0){
file.remove(name.of.excel.file)
}
# Avoid storing empty workbook
if(length(names(xo)) != 0){
saveWorkbook(xo, name.of.excel.file)
}
}
# Close progressbar
close(heatmapOutputProgressBar)
# report number of skipped heatmaps
if(skipped > 0 & skipped != 1){
message("[xlsxOutput] ", as.character(skipped), " out of ", as.character(total.number), " excel files were skipped, because they already exist!")
} else if(skipped > 0 & skipped == 1){
message("[xlsxOutput] ", as.character(skipped), " out of ", as.character(total.number), " excel file was skipped, because it already exists!")
}
# Store the last parameter
oldParamXlsxOutput <- newParameters
# Store the parameters for this run
if(number.of.rows.parameters == 0){
saveRDS(
oldParamXlsxOutput,
file=bfcnew(bfc, "Parameters for xlsxOutput()", ext="RDS")
)
} else if(number.of.rows.parameters == 1){
saveRDS(
oldParamXlsxOutput,
file=bfc[[bfcquery(bfc, "Parameters for xlsxOutput()")$rid]]
)
}
# change directory to parent directory
setwd(parent.directory)
# message("[xlsxOutput] Finished.")
}
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.